ZooMSS Dynamic Model Comparison

Author

ZooMSS Analysis

Published

August 13, 2025

Overview

This document compares ZooMSS dynamic model outputs across different chlorophyll scenarios to examine how environmental forcing affects zooplankton community dynamics.

Model Scenarios

  • Low Chlorophyll (0.01 mg m⁻³): Oligotrophic conditions representing nutrient-poor environments
  • Medium Chlorophyll (0.1 mg m⁻³): Mesotrophic conditions with moderate productivity
  • High Chlorophyll (4.0 mg m⁻³): Eutrophic conditions with high productivity
  • Linear Chlorophyll: Gradually increasing chlorophyll over time
  • Seasonal Chlorophyll: Seasonal variation patterns in chlorophyll
library(tidyverse)
library(patchwork)

source("fZooMSS_Plot.R")

Load Model Results

# Load constant chlorophyll scenarios
load("20250806_chl0_01_0001.RData")  # 0.01 mg m-3 chl (oligotrophic)
out1 <- out

load("20250806_chl0_1_0001.RData")   # 0.1 mg m-3 chl (mesotrophic)
out2 <- out

load("20250806_chl4_0_0001.RData")   # 4.0 mg m-3 chl (eutrophic)
out3 <- out

# Load dynamic chlorophyll scenarios
load("20250806_linear_0001.RData")   # Linear increasing chl
out4 <- out

load("20250806_Seasonal_0001.RData") # Seasonal chl patterns
out5 <- out

Abundance Time Series Comparison

Compare abundance patterns across all chlorophyll scenarios to understand how different productivity levels affect zooplankton population dynamics.

(fZooMSS_Plot_AbundTimeSeries(out1) + ggtitle("Low Chlorophyll (0.01 mg m⁻³)")) /
  (fZooMSS_Plot_AbundTimeSeries(out2) + ggtitle("Medium Chlorophyll (0.1 mg m⁻³)")) /
  (fZooMSS_Plot_AbundTimeSeries(out3) + ggtitle("High Chlorophyll (4.0 mg m⁻³)")) /
  (fZooMSS_Plot_AbundTimeSeries(out4) + ggtitle("Linear Increasing Chlorophyll")) /
  (fZooMSS_Plot_AbundTimeSeries(out5) + ggtitle("Seasonal Chlorophyll Patterns"))

Biomass Time Series - All Species

Proportional biomass plots showing relative contribution of each species to total community biomass across scenarios.

((fZooMSS_Plot_BiomassTimeSeries(out1, proportional = TRUE) + ggtitle("Low Chlorophyll (0.01 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out2, proportional = TRUE) + ggtitle("Medium Chlorophyll (0.1 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out3, proportional = TRUE) + ggtitle("High Chlorophyll (4.0 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out4, proportional = TRUE) + ggtitle("Linear Increasing Chlorophyll")) /
    (fZooMSS_Plot_BiomassTimeSeries(out5, proportional = TRUE) + ggtitle("Seasonal Chlorophyll Patterns"))) +
  plot_layout(guides = 'collect')

Biomass Time Series - Key Species

Focus on major zooplankton functional groups to highlight ecological patterns and trophic dynamics.

# Define key species of ecological interest
spp <- c("Larvaceans", "Salps", "Jellyfish", "OmniCopepods", 
         "Euphausiids", "CarnCopepods", "Chaetognaths")

((fZooMSS_Plot_BiomassTimeSeries(out1, proportional = TRUE, species = spp) + ggtitle("Low Chlorophyll (0.01 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out2, proportional = TRUE, species = spp) + ggtitle("Medium Chlorophyll (0.1 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out3, proportional = TRUE, species = spp) + ggtitle("High Chlorophyll (4.0 mg m⁻³)")) /
    (fZooMSS_Plot_BiomassTimeSeries(out4, proportional = TRUE, species = spp) + ggtitle("Linear Increasing Chlorophyll")) /
    (fZooMSS_Plot_BiomassTimeSeries(out5, proportional = TRUE, species = spp) + ggtitle("Seasonal Chlorophyll Patterns"))) +
  plot_layout(guides = 'collect')

Results Summary

The comparison reveals how different chlorophyll scenarios drive distinct zooplankton community dynamics:

  • Oligotrophic conditions (0.01 mg m⁻³): Limited productivity constrains overall biomass
  • Mesotrophic conditions (0.1 mg m⁻³): Moderate productivity supports balanced community structure
  • Eutrophic conditions (4.0 mg m⁻³): High productivity may favor certain functional groups
  • Linear increase: Shows community response to gradually changing conditions
  • Seasonal patterns: Captures natural temporal variability and community cycles

These results demonstrate the ZooMSS model’s ability to capture environmental forcing effects on marine zooplankton communities across different productivity regimes.